LightGlue is a PyTorch library for local feature matching between image pairs. It implements a deep neural network that takes sparse keypoints and descriptors (extracted by models like SuperPoint, DISK, ALIKED, or SIFT) and outputs correspondences. The architecture uses stacked self- and cross-attention transformer layers with adaptive pruning (width and depth) for speed, achieving state-of-the-art accuracy at high throughput. The repository provides pretrained weights, a benchmark script, and a demo notebook. It is designed for inference only; training code is in a separate repository (glue-factory). The code is well-structured, with clean separation between feature extractors, the matcher, and utility functions. It supports FlashAttention and PyTorch compilation for performance.
This repository is the central index and deployment configuration for the trace.moe anime scene search engine. It contains no application code; the actual functionality is implemented in separate repositories (trace.moe-api, trace.moe-www, etc.). The primary artifact is a Docker Compose file that orchestrates the entire stack, including PostgreSQL, Milvus vector database, and the API server. This repo is useful for operators who want to deploy the trace.moe system, but developers looking for reusable code should look at the sub-repositories. The documentation provides clear, step-by-step deployment instructions. The system itself is an image-based scene search service that uses vector similarity search to identify anime scenes from screenshots.